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Image interpolation is important for computer vision. Most of the existing image interpolation methods are based on the optimization in the mean square error (MSE) sense. In this paper, we incorporate the structural similarity (SSIM) based metric into the framework of the nonlocal edge-directed image interpolation (NLEDI) method. In the proposed algorithm, a missing pixel is interpolated using the...
Network streams have become ubiquitous in recent years because of many dynamic applications. Such streams may show localized regions of activity and evolution because of anomalous events. This paper will present methods for dynamically determining anomalous hot spots from network streams. These are localized regions of sudden activity or change in the underlying network. We will design a localized...
A conventional approach to image analysis is to perform separately feature extraction at a low level (such as edge detection) and follow this with high level feature extraction to determine structure (e.g. by collecting edge points using the Hough transform. The original image Ray Transform (IRT) demonstrated capability to extract structures at a low level. Here we extend the IRT to add shape specificity...
In this paper, a new light pattern is proposed for three-dimensional reconstruction. This pattern has several interesting properties and is highly robust to deformation due to its topology. Moreover, the proposed pattern is based on triangulation meshes which allow us to construct arbitrarily a high number of unique key points. Furthermore, the graph permits to have information on connectivity between...
Current mining algorithms for attributed graphs exploit dependencies between attribute information and edge structure, referred to as homophily. However, techniques fail if this assumption does not hold for the full attribute space. In multivariate spaces, some attributes have high dependency with the graph structure while others do not show any dependency. Hence, it is important to select congruent...
This work is concerned with solving non-convex power optimization problems by introducing the concept of “nonlinear optimization over graph”. To this end, the structure of a given nonlinear real/complex optimization with quadratic arguments is mapped into a generalized weighted graph, where each edge is associated with a weight set constructed from the known parameters of the optimization (e.g., the...
Fundamental to the identification of the architecture and organization of complex systems is the detection of modules, also called communities or clusters, through the use of graph partition methods. In this paper, we extend one of the most popular graph partition methods, modularity, to jointly preserve the structure of multiple networks using the multi-view technique. Under the assumption that the...
Visual cryptography schemes (VCS) have been introduced by Naor and Shamir [NS94] and involve a dealer encoding a secret image into shares that are distributed to a number of participants. In general, the collection of subsets of participants that can recover the secret is organized in an access structure. In this paper we consider graph based access structures, where participants are nodes of a graph...
In the graph theory, a Hamiltonian path is defined as a path in a graph which includes every vertex exactly once. The proposed method divides the cover image into some m×n blocks and partitions the binary secret data into some vectors with the length of m*n. For each block, one Hamiltonian path is first found such that the LSB of pixels of the block along this path have the maximum similarity to the...
Automated monitoring of activities of elderly is very important in the field of elderly healthcare. While fast and precise detection of falls is critical in providing immediate medical attention, other activities like walking, sitting and lying down can provide valuable information for early diagnosis of potential health problems. Recently, wearable smart cameras have emerged as a new area of research,...
Video text often contains highly useful semantic information, the analysis of which can to a great extent facilitate video retrieving and understanding. In this paper, a novel method has been proposed to detect video text. Text character strokes display dense edge features in both horizontal and vertical directions. Therefore the authors create a text edge map on the basis of the Kirsch operators...
The Campbell-Stokes sunshine recorder is an instrument which can measure the solar radiation by using the scorch on the recorder card. It is short for C-S. The weak scorch and the strong scorch represent different solar radiation. The weak scorch is so hard to extract that the radiation represented by the weak scorch always be neglected. The present methods reduce the accuracy of extraction, because...
Edges of an image are considered a type of crucial information that can be extracted by applying detectors with different methodology. Edge detection is a basic and important subject in computer vision and image processing In this Paper we discuss several Digital Image Processing Techniques applied in edge feature extraction. Firstly, Linear filtering of Image is done is used to remove noises from...
The Scale Invariant Feature Transform (SIFT) feature can be used for an image distance measure. SIFT keypoints are mainly located on high-contrast regions of an image, such as object edges and textures, which are often visually important. Therefore, it can be said that if a resized image keeps SIFT features which the corresponding original image has, the resized image is visually acceptable. To the...
In this paper, we propose a method to align multiple images of the same category. Images with large variations are aligned via a smooth transition formed by some intermediate images. These intermediate images are found by shortest warping path algorithm on a directed complete graph. Moreover, the common regions in the images are discovered to further improve alignment performance. The experimental...
The research behind this paper is dedicated to building a tool for batch-procesing X-ray medical images in medical establishments. This paper proposes the approach to object detection and edge finding suitable for X-ray medical images and producing object boundaries in vector representation as polygons. The approach consists of detection stage and edge refinement stage and exploits a class-specific...
In this paper, we employ the non-local steering kernel regression to construct an effective regularization term for the single image super-resolution problem. The proposed method seamlessly integrates the properties of local structural regularity and non-local self-similarity existing in natural images, and solves a least squares minimization problem for obtaining the desired high-resolution image...
In this paper we propose a new image domain prior term for regularizing the super-resolution reconstruction algorithm. This term encourages preserving the local ramp structure around edges, in the reconstruction algorithm. Ramp at a pixel is defined as the steepest sequence of monotonically increasing (or decreasing) pixels among all feasible directions around the pixel. As described in previous work,...
Traditional upsampling methods apply spatial-invariant filtering across the entire image for efficiency, but often produce unsatisfactory artifacts around the edges. We propose a novel image upsampling algorithm that preserves the image structure, particularly around the edges, better than previous techniques. Our method computes a spline approximation to the edges in the image via bitmap tracing...
This paper proposes a method for human detection in crowded scene from static images. We introduce to combine edgelet and LBP features to obtain more discriminative representations for local area. To cope with partial occlusion, part detectors are learned using real AdaBoost in bootstrap way. Responses of part detectors are combined to form the final results. We test our approach on several common...
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